Image compression/decompression system employing pixel thinning-out and interpolation scheme

ABSTRACT

An improved image thinning-out processing scheme includes processes of performing pixel thinning-out operation and compressing image data; and determining a position of pixel to be thinned out along a first direction depending on the position thereof along a second direction perpendicular to the first direction.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to an imagecompression/decompression system, in particular, to an imagecompression/decompression system employing efficient pixel thinning-outand interpolation schemes.

An image compression/decompression system according to the presentinvention may be applied widely to various image processing applicationprograms, various device drivers (software) such as printer drivers,also, to various image processing apparatus/equipment processing colorimages.

2. Description of the Related Art

With regard to image compression/decompression techniques, variousschemes have been proposed. For example, Japanese laid-open patentapplication No. 7-221993 discloses a color image data thinning-outmethod, and a color image data compression method. In the methods,according to change rates in U data and V data representing colorcomponents, a size of pixel zone to be thinned out for each image blockis controlled. Specifically, as the change rate is larger, the size ofpixel zone to be thinned out is to be reduced. On the other hand, as thechange rate is smaller, the size of pixel zone to be thinned out is tobe enlarged. Thereby, an edge line of an image is prevented from beinglost due to thinning-out processing.

Thus, by utilizing a characteristic of human eyes, a thinning-out rateis appropriately selected for a color component according to a colorchange rate for each image block such as that including 8×8 pixels,16×16 pixels or the like. Thereby, effective image compression withoutremarkable apparent degradation in image quality may be attained.

However, according to the above-described methods disclosed by Japaneselaid-open patent application No. 7-221993, a considerable time may berequired for calculating change rates in U data and V data for eachimage block.

Furthermore, generally speaking, a natural image is likely to include alot of thin lines/edge lines extending horizontally or vertically whilea few of those extending obliquely. Therefore, when simply pixelsarranged vertically are thinned out as disclosed by the above-mentionedpatent publication as shown in FIG. 1, a lot of thin lines, edge linesand so forth included in a natural image may be completely lost duringimage data compressing processing.

SUMMARY OF THE INVENTION

An object of the present invention is to solve the above-mentionedproblem, and, to provide an image compression/decompression schemeshaving a pixel thinning-out/interpolation schemes, by which, efficientimage data compression/decompression can be attained by an effectivelyreduced data processing time, reduced data processing resources, butwithout remarkable apparent degradation in image quality during imagedata compression/decompression processing.

For this purpose, according to the present invention, as shown in FIG.2, pixels to be thinned out are determined to be those arrangedobliquely or in a staggering manner, not straightly vertically orhorizontally. Thereby, it is possible to prevent a lot of thin lines,edge lines and so forth extending horizontally or vertically included ina natural image from being lost through image data compressingprocessing.

Furthermore, by selecting pixels to be thinned out as shown in FIG. 4 ina staggering manner, in comparison to a case shown in FIG. 3, distancesbetween adjacent ones of the pixels to be thinned out become effectivelyelongated. Thereby, it is possible that, even when vertically extendingthin lines included in a natural image are lost partially by thethinning-out processing, this may not result in remarkable apparentdegradation of image quality.

In order to achieve such thinning-out processing obliquely or in astaggering manner, a position of a pixel to be thinned out for eachimage block is determined, according to a predetermined rule, in such amanner that the pixels thinned out are prevented from becoming adjacentto each other between image blocks adjacent to each other vertically andhorizontally. Thereby, it is possible to achieve thinning-out processingobliquely or in a staggering manner by a simple configuration either ona device (LSI or the like) or on a software program.

An image compressing scheme according to the present inventioncomprising:

performing pixel thinning-out operation and compressing image data; and

determining a position of pixel to be thinned out along a firstdirection depending on the position thereof along a second directionperpendicular to the first direction.

Thereby, it is possible to prevent thin lines/edge lines included in anoriginal image from being lost remarkably apparently while higher-ratedata compressing can be attained with a relatively simple configuration.

In the above-mentioned scheme, the position of pixel to be thinned outmay comprise a position with respect to each predetermined unit area ofthe relevant image including a predetermined number of pixels.

Thus, by performing image data compression processing for each unit areaof the relevant original image, it is possible to attain high speedcompression processing.

In the scheme, the positions of pixels to be thinned out along the firstdirection may be determined along the second direction such that thepositions of pixels to be thinned out do not align with one anotherbetween each pair of unit areas adjacent to one another along the seconddirection.

Control operation performing such a manner of processing may be easilyattained by configuring such that the positions of the thinned-outpixels with respect to the respective unit areas may be changedalternately every line of unit areas according to a simple rule, asshown in FIGS. 6A, 6B, 7, 8 and 9. Thus, the positions of thethinned-out pixels are located not continuos but intermittently, and,thus, it is possible to effectively prevent thin lines/edge linesincluded in an original image from being lost continuously. Thus, a highimage quality may be maintained even through image data compressing anddecompressing processes.

An image decompressing scheme according to the present inventioncomprises:

interpolating/generating thinned-out pixels; and

determining pixels to be used for the interpolation,

wherein pixels nearest to the thinned-out pixels may be selected for theinterpolation.

Thereby, high speed image decompressing processing may be attained whilea high image quality may be maintained through image data compressingand decompressing processes.

In the scheme, pixels not included in an original pixel block in whichthinned-out pixels are included may be applied forinterpolation/generation of the thinned-out pixels.

Thereby, it is possible to utilize pixels of various pixel blocks(located in various directions, particularly, vertical and horizontaldirections) for interpolation. Accordingly, thin lines/edge linesextending in various directions included in an original image may beeffectively prevented from being lost during image datacompressing/decompressing processing.

The pixel to be used for interpolation may be determined such thatpixels adjacent to an original pixel block (rectangular block) via shortsides thereof may be applied.

Thereby, it is possible to utilize pixels of various pixel blocks(located in various directions, particularly, vertical and horizontaldirections) for interpolation. Accordingly, thin lines/edge linesextending in various directions included in an original image may beeffectively prevented from being lost during image datacompressing/decompressing processing.

Another image decompressing scheme according to the present inventioncomprises:

performing interpolation of thinned-out pixels; and

determining a method of interpolation according to a pixel-numberchanging rate of pixel-number changing processing performed after theinterpolation such that a finer interpolation method be selected as thepixel-number changing rate at which the number of pixels is increasedbecomes larger.

Thereby, high speed decompressing processing may be attained, while ahigh image quality may be maintained during image datacompressing/decompressing processing.

In the scheme, a nearest pixel method (described later) may be appliedwhen the pixel-number changing rate is less than a first threshold, alinear interpolation method (well-known) is applied when thepixel-number changing rate falls within a range between the firstthreshold and a second threshold, and a three-order interpolation method(described later) is applied when the pixel-number changing rate is morethan the second threshold.

Thereby, it is possible to appropriately select an interpolation methodaccording to a size of image to be output afterinterpolation/decompression. In case merely a small image should bedisplayed as an output image, a less finer interpolation method may beapplied so that a time required for performing image datadecompression/interpolation may be effectively reduced. In contrastthereto, in case a relatively large image should be displayed, a finerinterpolation method may be applied so that remarkable image degradationthrough image data compression which is likely to be apparent in such acase may be effectively prevented.

Another image decompressing scheme according to the present inventioncomprises:

interpolating thinned-out pixels from not-thinned-out pixels; and

determining an interpolating method applied,

so that a less finer interpolation method may be applied for thinned-outpixels located nearer to the not-thinned-out pixels used for theinterpolation.

Thereby, high speed decompressing processing may be attained, while ahigh image quality may be maintained during image datacompressing/decompressing processing.

In the scheme, a plurality of interpolation methods may be selectivelyapplied for a single image and the interpolation method to be appliedmay be determined according to the center-to-center pixel distances fromthe not-thinned-out pixels.

Thereby, high speed decompressing processing may be attained, while ahigh image quality may be maintained during image datacompressing/decompressing processing.

The nearest pixel method may be applied for thinned-out pixels mostnearest to the not-thinned-out pixels used for interpolation, and atleast one of the linear interpolation method and third-orderinterpolation method may be applied for the other thinned-out pixels.

BRIEF DESCRIPTION OF THE DRAWINGS

Other objects and further features of the present invention will becomemore apparent from the following detailed description when read inconjunction with the following accompanying drawings:

FIG. 1 illustrates a state of image data thinning-out processing schemein the related art;

FIGS. 2, 3 and 4 illustrate basic concepts of image data thinning-outprocessing schemes according to the present invention;

FIG. 5 illustrates a block diagram of an image processing system towhich first through sixteenth embodiments of the present invention maybe applied;

FIGS. 6A and 6B illustrate an image data thinning-out processing schemeaccording to a first embodiment of the present invention;

FIG. 7 illustrates an image data thinning-out processing schemeaccording to a second embodiment of the present invention;

FIG. 8 illustrates an image data thinning-out processing schemeaccording to a third embodiment of the present invention;

FIG. 9 illustrates an image data thinning-out processing schemeaccording to a fourth embodiment of the present invention;

FIG. 10 illustrates processing illustrated with reference to FIGS. 6Aand 6B;

FIG. 11 illustrates processing of image data interpolation forinterpolating pixels thinned out as illustrated with reference to FIGS.6A and 6B;

FIG. 12 illustrates processing illustrated with reference to FIG. 8;

FIG. 13 illustrates processing illustrated with reference to FIG. 9;

FIG. 14 illustrates a basic image data interpolation pattern accordingto a fifth embodiment of the present invention;

FIGS. 15A through 15C illustrate various types of definition of adjacentpixels for illustrating the present invention;

FIGS. 16 and 17 illustrate specific interpolation processing examplesaccording to the fifth embodiment of the present invention;

FIG. 18 illustrates a basic image data interpolation pattern accordingto a sixth embodiment of the present invention;

FIG. 19 illustrates a specific interpolation processing examplesaccording to the sixth embodiment of the present invention;

FIG. 20 illustrates a basic image data interpolation pattern accordingto a seventh embodiment of the present invention;

FIG. 21 illustrates a specific interpolation processing examplesaccording to the seventh embodiment of the present invention;

FIG. 22 illustrates a basic image data interpolation pattern accordingto an eighth embodiment of the present invention;

FIG. 23 illustrates a specific interpolation processing examplesaccording to the eighth embodiment of the present invention;

FIGS. 24 and 25 illustrate a case where image data is enlarged in size(the number of pixels) after decompression/interpolation is performed;

FIG. 26 illustrates processing described with reference to FIGS. 18 and19;

FIG. 27 illustrates processing described with reference to FIGS. 24 and25; and

FIGS. 28 through 35 illustrate processing according to ninth throughsixteenth embodiments of the present invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

Referring to the drawings, an image compressing/decompressing apparatuswhich realizes an image compressing/decompressing method according tothe present invention will now be described. In addition, this imagecompressing/decompressing method is realizable also on an informationrecording medium storing a software program which is executed by ageneral-purpose computer as will be described.

FIG. 5 is a circuit block diagram showing an example of a configurationof an image compressing/decompressing apparatus which realizes an imagecompressing/decompressing method according to the present invention.

As shown in FIG. 5, a printer apparatus 30 which carries out printingoutput image data read out from a hard disk drive unit HDD 10 whichstores original image data is connected with a personal computer PC 20which performs image compression processing, and images having undergonethe image processing by the PC 20 is transferred to the printerapparatus 30 via a data bus 40.

In a random access memory RAM 1 (21) image data read out from the harddisk drive unit HDD 10 is written, so that the personal computer PC 20may perform image compression thereon. A CPU 1 (22) manages and controlsthe entire personal computer PC 20. By using a random access memory RAM2 (31), a CPU 2 (32) of the printer apparatus 30 performs image datadecompressing operation on image data. The CPU2 manages and controls theentire printer apparatus 30.

When original image data stored in the hard disk drive unit HDD 10 is tobe printed out by the printer apparatus 30, the original image data iscompressed by the personal computer PC 20, and the compressed image datais transmitted to the printer apparatus 30 through the data bus 40. Bythe image compression processing, since the amount of transmitting datato the printer apparatus 30 is reduced, the transmitting time isshortened, and even considering the time required for image compressionand image decompressing of the original image data, high-speed print-outoperation becomes realizable.

First, the original image data recorded in the hard disk drive unit HDD10 is read out by the CPU 1 (22) of the personal computer PC 20, and iswritten into a reading area 21 a of the random access memory RAM 1 (21)according to instructions given by the CPU 1 (22).

The CPU 1 (22) reads out the original mage data from the random accessmemory RAM 1 (21) appropriately, and performs image compressionprocessing thereon accordingly.

The CPU 1 (22) writes the thus-compressed data into a compression area21 b of the random access memory RAM 1 (21), and stores theretemporarily.

After that, the CPU1 (22) gives instructions to the random access memoryRAM 1 such that the compressed data is read out therefrom, and, via thedata bus 40, it is transferred to the random access memory RAM 2 (31) inthe printer apparatus 30, and, is written to a transfer area 31 athereof.

The CPU 2 (32) of the printer apparatus 30 reads out the compressed datafrom the transfer area 31 a of the random access memory RAM 2 (31),obtains decoding values therefrom, performs decompressing processing onthe compressed image data, and thus, reproduces a decompressed imagehaving the number of pixels same as that of the original image data.

Then, the CPU 2 32 writes the decompressed image data into adecompression area 31 b of the random access memory RAM 2 (31), andstores there, temporarily.

Then, the CPU2 32 reads out the decompressed data from the random accessmemory RAM 2 (31), and, through predetermined processes, thedecompressing image data is printed out on a print paper.

The predetermined processes may include a size-change process by whichthe number of pixels of the image data is changed according toinstructions given by a user or the like.

The image compression processing carried out by the personal computer 20and the image decompressing processing carried out by the printerapparatus 30 will now be described based on FIGS. 6A and 6B first, andthen, following figures, in sequence.

FIG. 6A illustrates a concept of a process of compressing an image blockof 2×3 pixels into an image block of 2×2 pixels. FIG. 6B illustrates astate of thin lines A and B included in an original image affected bythe above-mentioned compression operation.

In this example, as shown in the figures, an image block of originalimage (original block), from which pixels are thinned out, has n pixelsvertically and m pixels horizontally, and, thus, has n×m pixels.Further, an image block which is thinned out from the above-mentionedimage block (thinning-out block) of original image has n pixelsvertically, and x pixels horizontally, and thus, has n×x pixels. Then, acompressed block obtained after the compression (compressed block) has npixels vertically, and (m−x) pixels horizontally, and, thus, has n×(m−x)pixels.

As shown in FIGS. 6A and 6B, in this example, n=2, m=3, x=1. Thus, fromthe original block of 2×3 pixels, the thinning-out block of 2×1 pixelsis thinned out, and, then, the compressed block of 2×2 pixels remains.

Specifically, as shown in the figures, according to the presentinvention, a position of the thinning-out block with respect to theoriginal block is changed alternately along the vertical direction. Inthe example shown in the figures, on a first line, the thinning-outblock is located at the left end of the original block, then, on asecond line, differently, the thinning-out block is located at the rightend of the original block, then, on a third line, the left end, . . . .Thus, the position of the thinning-out block with respect to theoriginal block is determined depending on the position along thevertical direction.

Thus, above-mentioned thinning-out processing by an oblique manner orstaggering manner can be attained, as shown in the figures. Thereby, asshown in FIG. 6B, pixels on the thin lines or edge lines A (verticallyextending) and B (horizontally extending) are lost by thinning-outprocessing only partially, so that the original image may be preventedfrom being remarkably apparently degraded.

FIGS. 6A and 6B illustrate the example in which the thinning-out blockof n×x is thinned out with respect to the original block of n×m.However, the present invention may also be applied to a case thevertical direction and horizontal direction are reversed from oneanother, where the thinning-out block of x×n is thinned out with respectto the original block of m×n, by a similar manner.

Then, the thus-obtained compressed image data having 2×2 blocks may befurther compressed by a well-known BTC (Block Truncation Coding)compressing scheme by which a lossy compressing scheme, and, thereby,the rate of compression of image data can be further improved.

Next, an image interpolation processing method of carrying outdecompressing of the compressed blocks obtained through imagecompression carried out by thinning-out processing as described abovewill now be described.

In case an image compressed into the compressed blocks each having 2×2pixels as shown in FIG. 6A are decompressed into decompressed blocks(corresponding to the original blocks) each having 2×3 pixels, the imagedata of each pixel of the above-mentioned thinned-out block whichincludes 2×1 pixels is obtained by interpolation by a nearest pixelmethod in which image data of pixels of the compressed blocks adjacentto the short sides of the thinned-out block is used for determiningimage data of the pixels of the thinned-out block.

For example, the thinned-out block ab shown in FIG. 6A has thecompressed blocks gj and kn₁ adjacent thereto via the short sidesthereof. The compressed block ‘gj’ of 2×2 pixels includes a pixel ‘g’, apixel ‘h’, a pixel ‘i’, and a pixel ‘j’, and the compressed block kn₁ of2×2 pixels includes a pixel ‘k’, a pixel ‘l’, a pixel m₁, and a pixeln₁. In this case, the image data of the pixel h adjacent to the upperpixel a of the thinned-out block ab via the short side thereof is usedas it is as the image data of the pixel a. Similarly, the image data ofthe pixel k adjacent to the pixel b of the thinned-out block ab via thebottom short side thereof is used as it is as the image data of thepixel b. Thus, interpolation is performed by the nearest pixel method.

Accordingly, for example, as shown in FIG. 6B, in case the perpendicularthin line A exists on the pixels g, h, and a, b, k, and l, as the pixela uses the image data of the pixel h, and the pixel b uses the imagedata of the pixel k as mentioned above through interpolation, the 2pixels a and b can restore the thin line A properly.

However, if the compressed blocks adjacent to the thinned-out block viathe long sides thereof are used for interpolation, that is, if, for thepixel a, the image data of the pixel e is used, and, for the pixel b,the image data of the pixel f is used, the 2 pixels may be lost for thethin line A. However, such a method may also be applied.

In such a case where the interpolation is performed by the nearest pixelmethod employing compressed blocks adjacent to the thinned-out block viathe long sides thereof, both the pixel e and the pixel o are in an equaldistance from the pixel a, and, similarly, both the pixel f and thepixel p are in an equal distance from the pixel b, the following methodis employed for determining the pixel to be used for the interpolation.That is, the image data of the pixel of the compressed block whichconstitutes the adjacent original image block to which the thinning-outblock does not belong is used. Accordingly, for the pixel a, the imagedata of the pixel e is used, and, for the pixel b, the image data of thepixel f is used for the interpolation.

In fact, in a case the horizontal thin line B exists on the pixels c, e,and a, o, and q, as shown in FIG. 6B, when the interpolation is made byusing the image data of the compressed block of the 2×2 pixels adjacentto the thinned-out block ab via the long side thereof, the image datafor one pixel of the thin line B can be correctly restored as, for thepixel a, the image data of the pixel e is used, and, also, for the pixelb, the image data of the pixel f is used.

However, if, in this case, the interpolation is made by employing thecompressed block adjacent to the thinned-out block ab via the short sidethereof, as, for the pixel a, the image data of the pixel h is used,and, also, for the pixel b, the image data of the pixel k is used, onepixel may be lost for the horizontal thin line B. However, even in thiscase, only the number of pixels corresponding to the length of the shortside, i.e., one pixel is lost for one block.

Thus, by employing the image data of the compressed block adjacent tothe thinned-out block via the short sides thereof for interpolation, itis possible to efficiently reduce the number of pixels which are losttherethrough even when loss of pixels concerning a thin line or an edgeline occurs therein. Accordingly, even employing the nearest pixelmethod, which requires merely a reduced processing time, it is possibleto prevent the image quality from remarkably degraded, with effectivelyreducing the processing time for the interpolation.

When image size-change (particularly, image magnification) processing ismade in case an image after decompression is output, for example, if thesize-change rate (at which the number of pixels is changed) is largerthan a predetermined first threshold (for example, larger than ‘1’,i.e., the number of pixels is increased), a well-known-linearinterpolation method is employed instead of the above-described nearestpixel method. That is, for example, in case the above-mentionedcompressed block of 2×2 pixels is decompressed as shown in FIG. 6A, therespective pixels of the plurality of compressed blocks adjacent to therelevant thinned-out block nearest to the relevant pixel of thethinned-out block are used for determining the image data of therelevant pixel.

For example, in the example shown in FIG. 6A, for the pixels a and b ofthe thinning-out block ab, the image data of the nearest pixels of thecompressed blocks ‘cf’ and ‘or’ adjacent to the relevant thinned-outblock ab via the long sides thereof are used for interpolation todetermine the image data of the pixels a and b, as follows:

As the image data of the pixel a of the thinned-out block ab, the imagedata of the average value {(e+o)/2} of the pixels e and o is used; and

as the image data of the pixel b, the image data of the average value{(f+p)/2} of the pixels f and p is used.

The reason for employing the linear interpolation instead of the nearestpixel method in case where image magnification processing is performedis as follows:

In such a case, when only one pixel is employed for determining theimage data of a thinned-out pixel according to the nearest pixel method,unnaturalness due to the interpolation may become remarkable. Therefore,the linear interpolation method which may provide tone smoothness moreeffectively than in the case of employing the nearest pixel method, ingeneral, is applied. Thereby, it may be possible to prevent suchunnaturalness from being apparent in the reproduced/decompressed image.

Furthermore, in case a decompressed image is magnified still moregreatly, i.e., the size-change rate is more than a second predeterminedthreshold (for example, 2, i.e., the number of pixels is increased morethan twice), instead of the linear interpolation method, a third-orderinterpolation method is used in which, by using a three-ordercalculation formula, the image data of the thinned-out pixel(interpolation pixel) is determined by using all the compressed blocksadjacent to the relevant thinned-out block.

For example, in the example shown in FIG. 6A, in case the pixel a of thethinned-out block ab is determined when the above-mentioned compressedblock of 2×2 pixels is decompressed, the following scheme is applied:

In this case, the image data of 16 pixels of all the four compressedblocks cf, gj, kn₁ and or adjacent to the thinned-out block ab are used.

Specifically, the following three-order formula (1) is used:f(a)=f(c)C(x _(c) −x _(a))C(y _(c) −y _(a))+f(d)C(x _(d) −x _(a))C(y_(d) −y _(a) + . . . + f(q)C(x _(q) −x _(a))C(y _(q) −y _(a))+f(r)C(x_(r) −x _(a))C(y _(r) −y _(a))  (1)where:

f(a) denotes interpolated image data of the pixel a; f(c) denotes theimage data of the pixel c; . . . , f(q) denotes the image data of thepixel q; and f(r) denotes the image data of the pixel r. x_(a) and y_(a)denote x-coordinate value and y-coordinate value of the pixel a on colorchromaticity coordinate plane, respectively. (x_(c), x_(d), . . . ,x_(q), x_(r)) and (y_(c), y_(d), . . . , y_(q), y_(r)) denotex-coordinate values and y-coordinate values of pixels c, d, . . . , qand r on the color chromaticity coordinate plane, respectively.

C(t) is an approximation formulas of a function {sin πt/πt} whichconstitutes a sampling theorem, and one of the following formulas (2),(3) and (4) is applied according to the value of the variable t, asfollows:C(t)=1−2t ² +|t| ³, in case 0≦|t|<1  (2);C(t)=4−8|t|+5t ² −|t| ³, in case 1≦|t|<2  (3);C(t)=0, in case 2≦|t|  (4)

According to the three-order interpolation method, as the plurality ofpixels of compressed blocks present in the periphery of the relevantpixel are utilized, although the processing speed becomes decreased, itis possible to provide further higher image quality in comparison to thecase of employing the linear interpolation method.

The above-mentioned first and second predetermined thresholds should bedetermined according to various conditions such as image displayperformance of an image compression/decompression apparatus used, anobservation distance at a time of observation thereof, and so forth.Accordingly, the above-mentioned values (for example, ‘1’ and ‘2’) aremerely examples.

FIGS. 10 and 11 are flow charts showing flows of processing of theabove-described image compressing/decompressing methods. That is, FIG.10 is a flow chart illustrating an example of a flow of processingaccording to an image compression technology according to the firstembodiment of the present invention, and FIG. 11 is a flow chartillustrating an example of a flow of image decompression processingaccording to the present invention for decompressing image datacompressed according to the processing illustrated in FIG. 10.

The flow of the image compression processing shown in FIG. 10 will nowbe described.

When compressing horizontally original image blocks each including 2×3pixels which is a unit area to be compressed, the block of 2×1 pixels tobe thinned out is located in the same position with respect to eachoriginal block (for example, the right end) throughout the same line (ina step S1). On the other hand, with respect to the vertical direction,the location of the thinned-out block of 2×1 pixels with respect to eachoriginal block of 2×3 pixels is determined so that the thinned-out blockis not adjacent to any thinned-out block on the immediately precedingline (for example, the left end in case the thinned-out block is locatedat the right end on the immediately preceding line) (in a step S2).

Furthermore, as for the compressed blocks each including 2×2 pixelsafter thinning out the thinning-out blocks each of 2×1 pixels from theoriginal blocks each of 2×3 pixels, lossy compression is performedthereon based on the BTC method (in a step S3).

Then, in a step S4, when all the original blocks have not undergone thethinning-out processing, the above-described process (steps S1 throughS3) is repeated. After all the original blocks have been processed, theimage compressing processing is finished.

The flow of image decompressing processing shown in FIG. 11 will now bedescribed.

Image data having 2×2 pixels which is a compressed block is read (in astep S11).

Then, a size-change rate α (pixel number change rate) on the relevantimage for size change processing (pixel number change processing)performed when the decompressed image is output is determined (in a stepS12).

In case the size-change rate is not more than the first predeterminedthreshold (for example, “1”), interpolation is performed according tothe nearest pixel method such that the image data of each pixel of thethinned-out block is determined from the image data of the pixeladjacent thereto via the short side of the block, as described above (ina step S13).

In case the size-change rate is more than the first predeterminedthreshold (for example, “1”) and also not more than the secondpredetermined threshold (for example, “2”), interpolation is performedaccording to the linear interpolation method such that the image data ofeach pixel of the thinned-out block is determined from the image data ofthe pixels nearest thereto of the plurality of compressed blocksadjacent to the thinned-out block, for example, via the long sidesthereof, as described above (in a step S14).

In case the size-change rate is more than the second predeterminedthreshold (for example, “2”), interpolation is performed according tothe three-order interpolation method such that the image data of eachpixel of the thinned-out block is determined from the image data of therespective pixels of all the compressed blocks adjacent to thethinned-out block, as described above (in a step S14).

With reference to FIG. 7, image compression scheme and interpolationscheme according to a second embodiment of the present invention in casethe number of pixels in a vertical direction of thinning-out/thinned-outblock is equal to or more than three will now be described.

In FIG. 7, in case color image data is compressed, each of originalimage blocks from which thinning-out blocks are thinned out/removedincludes 3×3 pixels. In the figure, 3×2 pixels shown as a white portionof each original image block are extracted as a compressed block afterimage compression, and 3×1 pixels shown as a hatched portion at theright or left end of each original image block are removed as athinned-out block.

Specifically, during image data compression according to the secondembodiment of the present invention illustrated by FIG. 7, on thehorizontal direction, the position of the thinning-out/thinned-out blockwith respect to each original image block is the same for the same line.However, on the vertical direction, the position of thethinning-out/thinned-out block with respect to each original image blockis determined so that the thinning-out/thinned-out block may not beadjacent to or may not align with any thinning-out/thinned-out block onthe immediately preceding line. For example, in the example shown inFIG. 7, the position of the thinning-out/thinned-out block is the rightend with respect to each original image block on the first line, but isthe left end on the second line, then is the right end on the thirdline, . . . . By thus proceeding with thinning-out processing byrepeating for respective lines of original image blocks according to thesimple rule, the thinning-out/thinned-out blocks are positioned so thatthey are not adjacent to or not aligned with each other, as shown inFIG. 7, for example.

Also in this embodiment, it is possible that the horizontal directionand vertical direction are replaced with one another. That is, theposition of the thinning-out/thinned-out block is the same on the samecolumn for the vertical direction, and, the position thereof isdetermined so that the thinning-out/thinned-out block may not adjacentto or may not align with any thinning-out/thinned-out block on theimmediately preceding column.

Thereby, as the respective thinning-out/thinned-out blocks are notadjacent to or not aligned with each other between any adjacent originalimage blocks, a situation that all the pixels arranged straightly inhorizontal direction or vertical direction are thinned out/removed bycompression processing can be positively prevented. Accordingly, it ispossible to prevent thin line/edge lines extending vertically orhorizontally from being lost remarkably through image compression anddecompression processing. Thus, it is possible to maintain a high imagequality.

Then, after the above-described thinning-out processing, theabove-mentioned BTC compression (lossy compression) is performed on thecompressed blocks, and, thereby, the compression rate is furtherincreased.

Image interpolation scheme in image decompression of the thus-obtainedcompressed image data will now be described.

According to the second embodiment, as shown in FIG. 7, the number ofpixels of each thinning-out/thinned-out block in the vertical directionis more than two. Accordingly, both vertical end pixels of thethinning-out/thinned-out block are determined by the pixels of thecompressed blocks adjacent to the thinning-out/thinned-out block via theshort sides thereof in the nearest pixel method as in theabove-described first embodiment. In contrast thereto, as to theintermediate pixel, the image data thereof is determined by the imagedata of the pixel of the compressed block adjacent to thethinning-out/thinned-out block via the long side thereof but notincluded in the original image block in which the relevantthinning-out/thinned-out block is included.

Specifically, in the example shown in FIG. 7, thethinning-out/thinned-out block ac of 3×1 pixels includes pixels a, b andc; the compressed block jo of 3×2 pixels includes j, k, l, m₁, n₁, and oadjacent to the above-mentioned thinning-out/thinned-out block ac viathe top short side thereof; the compressed block pu of 3×2 pixelsincludes p, q, r, s, t, and u adjacent to the above-mentionedthinning-out/thinned-out block ac via the bottom short side thereof; andthe compressed block di of 3×2 pixels includes d, e, f, g, h, and iadjacent to the above-mentioned thinning-out/thinned-out block ac viathe left long side thereof but not included in the original image blockin which the thinning-out/thinned-out block ac is included.

In this case, according to the above-described scheme, the image data ofthe top pixel a of the thinning-out/thinned-out block ac is determinedas the image data of the pixel l adjacent thereto on the top side; theimage data of the bottom pixel c of the thinning-out/thinned-out blockac is determined as the image data of the pixel p adjacent thereto onthe bottom side; and the image data of the intermediate pixel b of thethinning-out/thinned-out block ac is determined as the image data of thepixel h adjacent thereto on the left side.

Thereby, similarly to the case of the above-described first embodimentillustrated in FIGS. 6A and 6B, as the pixels of thethinning-out/thinned-out block adjacent to the short sides thereof aredetermined by using the pixels of the compressed blocks adjacent to thethinning-out/thinned-out block via the short sides thereof according tothe nearest pixel method, it is possible to effectively reduce thenumber of pixels lost from thin line/edge line extending verticallyduring image compression and decompression processing.

Furthermore, as to the intermediate pixel of thethinning-out/thinned-out block, the image data thereof is determined byusing the nearest pixel but adjacent to the pixel to be determined inthe direction other than the direction of the above-mentioned case ofinterpolation manner for the pixels adjacent to the short sides of thethinning-out/thinned-out block. Accordingly, the direction ofinterpolation is not fixed to vertical or horizontal, but variousdirections are used for the interpolation. Thereby, it is possible toeasily maintain the image quality from remarkably degraded.

Thus, according to the second embodiment, same as in the firstembodiment, as the pixel thinning scheme is improved, it is possible tomaintain a high image quality during image compression and decompressionby interpolation although employing the nearest pixel method whichmerely requires a reduced processing time. Accordingly, it is possibleto attain high speed interpolation processing.

In the second embodiment, the flows of processing of image compressionand image decompression are the same as those of the above-describedfirst embodiment illustrated in FIGS. 10 and 11. However, different fromthe first embodiment, the original image block has 3×3 pixels, and thethinning-out/thinned-out block has 3×1 pixels, as mentioned above.Especially, according to the second embodiment, as the number of pixelsof the thinning-out/thinned-out block along the vertical direction ismore than two, image data of the intermediate pixel(s) is determined indecompression processing by using the pixel(s) of the compressed blockadjacent to the thinning-out/thinned-out block but not included in theoriginal image block in which the thinning-out/thinned-out block isincluded, as described above.

Although the above-described second embodiment employs the originalblock of 3×3 pixels and thinning-out/thinned-out block of 3×1 pixels,the basically same concept may be applied to a case where the number ofpixels along the vertical direction increases more than three, i.e.,four, five, . . . . That is, the concept of the second embodiment mayalso be applied to a case employing the original block of 4×3 pixels andthinning-out/thinned-out block of 4×1 pixels . . . . In such a case, thenumber of the above-mentioned intermediate pixels becomes more than one,i.e., two, three, . . .

With reference to FIG. 8, image compression scheme and interpolationscheme according to a third embodiment of the present invention in casethe number of pixels of thinning-out/thinned-out block is half thenumber of the original image block will now be described.

In FIG. 8, in case color image data is compressed, each of originalimage blocks from which thinning-out blocks are thinned out includes 2×4pixels. In the figure, 2×2 pixels shown as a white portion of eachoriginal image block are extracted as a compressed block after imagecompression, and 2×2 pixels shown as a hatched portion at the right orleft end of each original image block are removed off as a thinned-outblock.

Specifically, during image data compression according to the thirdembodiment of the present invention illustrated by FIG. 8, on thehorizontal direction, the position of the thinning-out/thinned-out blockwith respect to each original image block is the same for the same line.However, on the vertical direction, the position of thethinning-out/thinned-out block with respect to each original image blockis determined so that the thinning-out/thinned-out block may not beadjacent to or may not align with any thinning-out/thinned-out block onthe immediately preceding line. For example, in the example shown inFIG. 8, the position of the thinning-out/thinned-out block is the rightend with respect to each original image block on the first line, but isthe left end on the second line. By proceeding with thinning-outprocessing by repeating for respective lines of original image blocksaccording to the simple rule, the thinning-out/thinned-out blocks arepositioned so that they are not adjacent to or not aligned with eachother, as shown in FIG. 8, for example.

Also in this embodiment, it is possible that the horizontal directionand vertical direction are replaced with one another. That is, theposition of the thinning-out/thinned-out block is the same on the samecolumn for the vertical direction, and, the position thereof isdetermined so that the thinning-out/thinned-out block may not adjacentto any thinning-out/thinned-out block on the immediately precedingcolumn.

Thereby, as the respective thinning-out/thinned-out blocks are notadjacent to or not aligned with each other between any adjacent originalimage blocks, a situation that all the pixels arranged straightly inhorizontal direction or vertical direction are thinned out/removed bycompression processing can be positively prevented. Accordingly, it ispossible to prevent thin line/edge line extending vertically orhorizontally from being lost remarkably through image compression anddecompression processing. Thus, it is possible to easily maintain a highimage quality.

Then, after the above-described thinning-out processing theabove-mentioned BTC compression (lossy compression) is performed on thecompressed blocks, and, thereby, the compression rate is furtherincreased.

Image interpolation scheme in image decompression of the thus-obtainedcompressed image data will now be described.

In order to obtain a decompressed block of 2×4 pixels from thecompressed block of 2×2 pixels through decompression in the exampleshown in FIG. 8, the above-mentioned thinning-out/thinned-out block isobtained by interpolation by using the pixels of the compressed blocksadjacent to the thinning-out/thinned-out block via the short sidesthereof according to the nearest pixel method.

Specifically, in the example shown in FIG. 8, thethinning-out/thinned-out block ad of 2×2 pixels includes pixels a, b, cand d; the compressed block il of 2×2 pixels includes i, j, k and ladjacent to the above-mentioned thinning-out/thinned-out block ad viathe top short side thereof; the compressed block m₁p of 2×2 pixelsincludes m₁, n₁, o and p adjacent to the above-mentionedthinning-out/thinned-out block ad via the bottom short side thereof.

In this case, according to the above-described scheme, the image data ofthe top pixel a of the thinning-out/thinned-out block ad is determinedas the image data of the pixel j adjacent thereto on the top side; theimage data of the top pixel b of the thinning-out/thinned-out block adis determined as the image data of the pixel m₁ adjacent thereto on thebottom side; the image data of the top pixel c of thethinning-out/thinned-out block ad is determined as the image data of thepixel l adjacent thereto on the top side; the image data of the toppixel d of the thinning-out/thinned-out block ad is determined as theimage data of the pixel o adjacent thereto on the bottom side, as shownin FIG. 8.

Thereby, similarly to the case of the above-described first embodimentillustrated in FIGS. 6A and 6B, as the pixels of thethinning-out/thinned-out block adjacent to the short sides thereof aredetermined by using the pixels of the compressed blocks adjacent to thethinning-out/thinned-out block via the short sides thereof according tothe nearest pixel method, it is possible to effectively reduce thenumber of pixels lost from thin line/edge line extending verticallyduring image compression and decompression processing. Thereby, it ispossible to easily maintain the image quality. Thus, even when thinline/edge line is lost through compression and decompression, the numberof pixels lost can be effectively reduced.

Thus, also according to the third embodiment, same as in the firstembodiment, as the pixel thinning scheme is improved, it is possible tomaintain a high image quality during image compression and decompressionby interpolation although employing the nearest pixel method whichrequires reduced processing time. Accordingly, it is possible to attainhigh speed interpolation processing.

In the third embodiment, as shown in FIG. 12, when compressinghorizontally original image blocks each including 2×4 pixels which is aunit area to be compressed, the block of 2×2 pixels to be thinned out islocated in the same position with respect to each original block (forexample, the right end) throughout the same line (in a step S21). On theother hand, with respect to the vertical direction, the location of thethinned-out block of 2×2 pixels with respect to each original block of2×4 pixels is determined so that the thinned-out block is not adjacentto or not aligned with the thinned-out block on the immediatelypreceding line (for example, the left end in case the thinned-out blockis located at the right end on the immediately preceding line) (in astep S22).

Furthermore, as for the compressed blocks each including 2×2 pixelsafter thinning out the thinning-out blocks each of 2×2 pixels have beenthinned out from the original blocks each of 2×4 pixels, lossycompression is made based on the BTC method (in a step S23).

Then, in a step S24, when all the original blocks have not undergone thethinning-out processing, the above-described process (steps S21 throughS23) is repeated. After all the original blocks have been processed, theimage compressing processing is finished.

The flow of processing of image decompression is the same as that of theabove-described first embodiment illustrated in FIG. 11. However,different from the first embodiment, the original image block has 2×4pixels, and the thinning-out/thinned-out block has 2×2 pixels, asmentioned above.

With reference to FIG. 9, image compression scheme and interpolationscheme according to a fourth embodiment of the present invention in casethe number of pixels of the thinning-out/thinned-out block is smallerthan half the number of pixels of the original image block will now bedescribed.

In FIG. 9, in case color image data is compressed, each of originalimage blocks from which thinning-out blocks are thinned out includes 2×3pixels. In the figure, 2×1 pixels shown as a white portion of eachoriginal image block are extracted as a compressed block after imagecompression, and 2×2 pixels shown as a hatched portion at the right orleft end of each original image block are removed as a thinned-outblock.

Specifically, during image data compression according to the fourthembodiment of the present invention illustrated by FIG. 9, in thehorizontal direction, the position of the thinning-out/thinned-out blockwith respect to each original image block is the same for the same line.However, in the vertical direction, the position of thethinning-out/thinned-out block with respect to each original image blockis determined so that the compressed block to be left, instead of thethinning-out/thinned-out block, may not be adjacent to or may notaligned with any compressed block on the immediately preceding line. Forexample, in the example shown in FIG. 9, the position of the compressedblock is the left end with respect to each original image block on thefirst line, but is the right end on the second line. By proceeding withthinning-out processing by repeating for respective lines of originalimage blocks according to the simple rule, the compressed blocks arepositioned so that they are not adjacent to or not aligned with eachother, as shown in FIG. 9, for example.

Also in this embodiment, it is possible that the horizontal directionand vertical direction are replaced with one another. That is, theposition of the thinning-out/thinned-out block is the same on the samecolumn for the vertical direction, and, the position of the compressedblock is determined so that the compressed block to be left may notadjacent to or may not align with any compressed block on theimmediately preceding column.

Thereby, as the respective compressed blocks are not adjacent to or notaligned with each other between any adjacent original image blocks, asituation that all the pixels arranged straightly in horizontaldirection or vertical direction are thinned out/removed by compressionprocessing can be prevented. Accordingly, it is possible to prevent thinline/edge line extending vertically or horizontally from being lostthrough image compression and decompression processing. Thus, it ispossible to maintain high image quality.

Then, after the above-described thinning-out processing theabove-mentioned BTC compression (lossy compression) is performed on thecompressed blocks, and, thereby, the compression rate is furtherincreased.

According to the fourth embodiment, in comparison to the firstembodiment, the compression rate can be improved from 1.5 to 3.Accordingly, it is possible to effectively reduce a transmission timefrom the personal computer 20 to the printer apparatus 30.

Image interpolation scheme in image decompression of the thus-obtainedcompressed image data will now be described.

In order to obtain a decompressed block of 2×3 pixels from thecompressed block of 2×1 pixels through decompression in the exampleshown in FIG. 9, the above-mentioned thinning-out/thinned-out block isobtained by interpolation by using the pixels of the compressed blocksadjacent to the thinning-out/thinned-out block via the short sidesthereof according to the nearest pixel method.

Specifically, in the example shown in FIG. 9, thethinning-out/thinned-out block ad of 2×2 pixels includes pixels a, b, cand d; the compressed block gh of 2×1 pixels includes g and h adjacentto the above-mentioned thinning-out/thinned-out block ad via the topshort side thereof; the compressed block ef of 2×1 pixels includes e andf adjacent to the above-mentioned thinning-out/thinned-out block ad viathe left short side thereof; the compressed block ij of 2×1 pixelsincludes i and j adjacent to the above-mentionedthinning-out/thinned-out block ad via the bottom short side thereof; andthe compressed block kl of 2×1 pixels includes k and l adjacent to theabove-mentioned thinning-out/thinned-out block ad via the right shortside thereof, as shown in the figure.

In this case, according to the above-described scheme, the image data ofthe top pixel a of the thinning-out/thinned-out block ad is determinedas the image data of the pixel h adjacent thereto on the top side; theimage data of the bottom pixel b of the thinning-out/thinned-out blockad is determined as the image data of the pixel i adjacent thereto onthe bottom side; the image data of the top pixel c of thethinning-out/thinned-out block ad is determined as the image data of thepixel k adjacent thereto on the right side; and the image data of thetop pixel d of the thinning-out/thinned-out block ad is determined asthe image data of the pixel l adjacent thereto on the right side, asshown in FIG. 9.

Thereby, similarly to the case of the above-described first embodimentillustrated in FIGS. 6A and 6B, as the pixels of thethinning-out/thinned-out block adjacent to the short sides thereof aredetermined by using the pixels of the compressed blocks adjacent to thethinning-out/thinned-out block via these short sides thereof accordingto the nearest pixel method, it is possible to effectively reduce thenumber of pixels lost from thin line/edge line extending verticallyduring image compression and decompression processing. Accordingly, thedirection of interpolation is not fixed to vertical or horizontal, butvarious directions are used for the interpolation. Thereby, it ispossible to easily maintain the image quality. Thus, even when thinline/edge line is lost through compression and decompression, the numberof pixels lost can be effectively reduced.

In each of the above-mentioned second through fourth embodiments, it isalso possible to employ the above-described linear interpolation methodor three-order interpolation method instead of the nearest pixel method,as described above.

Thus, also according to the fourth embodiment, same as in the firstembodiment, as the pixel thinning scheme is improved, it is possible tomaintain a high image quality during image compression and decompressionby interpolation although employing the nearest pixel method whichrequires reduced processing time. Accordingly, it is possible to attainhigh speed interpolation processing.

In the fourth embodiment, as shown in FIG. 13, when compressinghorizontally original image blocks each including 2×3 pixels which is aunit area to be compressed, the block of 2×2 pixels to be thinned out islocated in the same position with respect to each original block (forexample, the right end) throughout the same line (in a step S31). On theother hand, with respect to the vertical direction, the location of thecompressed block of 2×1 pixels with respect to each original block of2×3 pixels is determined so that the compressed block is not adjacent toor not aligned with any compressed block on the immediately precedingline (for example, the left end in case the thinned-out block is locatedat the right end on the immediately preceding line) (in a step S32).

Furthermore, as for the compressed blocks each including 2×1 pixelsafter thinning out the thinning-out blocks each of 2×2 pixels have beenthinned out from the original blocks each of 2×3 pixels, lossycompression is made based on the BTC method (in a step S33).

Then, in a step S34, when all the original blocks have not undergone thethinning-out processing, the above-described process (steps S31 throughS33) is repeated. After all the original blocks have been processed, theimage compressing processing is finished.

The flow of processing of image decompression is the same as that of theabove-described first embodiment illustrated in FIG. 11. However,different from the first embodiment, the original image block has 2×3pixels, and the thinning-out/thinned-out block has 2×2 pixels, asmentioned above.

After that, embodiments of how to select one of, and/or to combine theabove-mentioned nearest pixel method, linear interpolation method andthree-order interpolation method according to positions ofthinning-out/thinned-out pixels to be generated from a compressed blockwith respect to the positions of pixels of the compressed block will nowbe described. According to the schemes of the embodiments which will bedescribed now, it is possible to prevent an image quality from beingremarkably apparently degraded during image compression anddecompression processes, even when relatively large areas are thinnedout through the compression process so as to increase the compressionrate.

FIG. 14 illustrates a basic interpolation pattern in an imageinterpolation method according to the embodiments which will bedescribed now. With regard to color image data, 5×5 pixels are used as aunit, and, when the 5×5 pixels are generated from 2×2 pixels (indicatedby black in the figure), two types of interpolation methods are used forpixels other than the pixels indicated by black. For example, in casethe pixels (indicated by gray in the figure) are adjacent to the pixelsof the black zone as shown in the figure, the first interpolation methodis applied to generate the pixels of the gray zone while the secondinterpolation method, different from the first interpolation method, isapplied to generated the other pixels (indicated by white).

FIGS. 12A through 12C illustrate definition of “adjacent pixels” appliedto the description below. First, FIG. 12A shows adjacent pixels (grayzone) of image area indicated by black. As shown in the figure, theadjacent pixels are those possessing a side or a vertex of the relevantimage area (black zone) in common. The meaning of “in common” in thiscase is a conceptual one, and, thus, may also be widely applied to acase respective pixels are spaced from each other. FIG. 12B showsadjacent pixels (gray zone) of the two sides q and q of the relevantimage area (black zone) in case the relevant image zone has arectangular shape as shown in the figure. FIG. 12C shows adjacent pixels(gray zone) of the respective four sides p, q, s and r of the relevantimage area (black zone). A term “pixel group” which will occur alsomeans a single pixel.

FIG. 16 illustrates one example of image interpolation method accordingto a fifth embodiment of the present invention. As shown in the figure,for the gray zone, the interpolation is performed according to thenearest pixel method, and, thus, the image data of the adjacent pixel ofthe black zone is applied as it is so that (1)→(1); (3)→(3); (5)→(5), .. . . With regard to the white zone, the linear interpolation method isapplied, and, thus, ((1)+(2))/2→(9); ((5)+(7))/2→(10); ((3)+(4))/2→(11);((5)+(6))/2→(12); ((7)+(8))/2→(13); ((6)+(8))/2→(14);((12)+(13))/2→(15).

FIG. 17 shows another example of the image interpolation methodaccording to the fifth embodiment of the present invention. Also in thisexample, same as in the example shown in FIG. 16, the image data of thepixels in the gray zone is determined by the nearest pixel method byusing the image data of the pixels in the black zone as shown in thefigure. However, the image data of the pixels in the white zone isdetermined according to the three-order interpolation method.

Specifically, assuming that the coordinate system of the original imageis of X-Y while the coordinate system of the image data after coordinatetransformation is of X′-Y′, the relationship therebetween can beexpressed by the following formulas (I) and (II) assuming that therelationship between both the coordinate systems is linear:x=ax′+by′+c  (I);y=dx′+ey′+f  (II)Accordingly, the relationship between both the coordinate systems can beobtained from calculating of the above-mentioned constants a, b, c, d, eand f by using corresponding actual coordinate values on six points. Inthe calculation, these six points are not necessarily to be latticepoints (integral coordinate values).

Then, by using the above-mentioned formulas (I) end (II), for all thepoints of an image obtained after the transformation, correspondingpoints on the original image are obtained, and, color information on thepoints on the original image is used as color information of the pointson the transformed image. However, as all the points on the originalimage may not be lattice points, desired color information should beobtained by using the color information of peripheral lattice points. Insuch a case, the above-mentioned three-order interpolation method isused for obtaining the desired color information by using the colorinformation on the peripheral lattice points.

Accordingly, the same manner may be applied to the case of interpolatingpixels in the white zone from pixels in the black/gray zones.Specifically, the pixels (1) through (16) in the black zone shown inFIG. 17 are assumed to be points G through V, and the pixel (17) in thewhite zone is assumed to be a point Z. Then, by using image data f(G)through f(V) on the 16 points G through V, the image data f(Z) on thepixel (17) is determined through interpolation (third-orderinterpolation), by using the following formulas (III) through (VI):f(Z)=f(G)C(x _(G) −x _(z))C(y _(G) −y _(Z))+f(H)C(x _(H) −x _(z))C(y_(H) −y _(Z))+ . . . +f(V)C(x _(V) −x _(z))C(y _(V) −y _(Z))  (III)C(t)=1−2t ² +|t| ³, in case 0≦|t|<1  (IV).C(t)=4−8|t|+5t ² −|t| ³, in case 1≦|t|<2  (V);C(t)=0, in case 2≦|t|  (VI)

There, C(t) represents an approximation formula of function sin πx/πxwhich expresses a sampling theorem, and the formulas (III) through (VI)are used for each component of R, G, B of color image data.

According to this method, as information of as many as 16 points isused, it is possible to provide a higher-quality image in comparison toa case of using the linear interpolation method.

At this time, in case m−x≧3 and n−y≧3 or 2x<m and 2y<n (see FIG. 14), aplurality of the above-described interpolation methods are selectivelyused. This is because, in such a case, it is necessary to select anappropriate one thereof according to the length of (m−x) and (n−y). Forexample, when the lengths of (m−x) and (n−y) are smaller (compressionrate is smaller), the linear interpolation method (less finerinterpolation method) may be applied for the white zone, while, whenthese lengths are larger (compression rate is larger), the three-orderinterpolation method (finer interpolation method) may be applied for thewhite zone. There, each of m, n, x and y represents the number ofpixels. In the example of FIG. 14, n=5; m=5, x=2, and y=2. In this case,the gray zone (to which the nearest pixel method is applied as mentionedabove) has the width of one pixel, as shown in the figure. This isbecause, as the image data of the gray zone is generated by using theblack zone as it is according to the nearest pixel method, the imagequality may be degraded if the gray zone has a wide area in comparisonto the area of the black zone.

FIG. 18 illustrates an example of a basic interpolation patternaccording to a sixth embodiment of the present invention. Similar toFIG. 14, 5×5 pixels are used as a unit of color image data, and, bydecompression through interpolation, 5×5 pixels are generated from 2×2pixels in a black zone. Then, for determining pixels other than theblack zone, a plurality of interpolation methods are selectively used.In particular, in the example of FIG. 18, different from theabove-described example shown in FIG. 14, the pixel having a distance βin a center-to-center basis from the pixel in the black zone which islongest among the distances α, β and γ is determined as a white pixel,and, the image data of the pixels in the gray zone are determinedaccording to a first interpolation method while the image data of thepixel in the white zone is determine by a second interpolation methodother than the first interpolation method.

Specifically, in a example shown in FIG. 19, the nearest pixel method isused for the gray zone, and the linear interpolation method is used forthe white zone. Thus, the image data of the pixels in the white zone isdetermined as the image data of the pixels adjacent theretorespectively, as follow, as shown in the figure: (1)→(1); (5)→(5);(3)→(3); . . . . On the other hand, the image data on the pixels in thewhite zone is determined according to the linear interpolation method asfollows: ((1)+(2))/2→(9); ((5)+(7))/2→(10); ((3)+(4))/2→(11);((5)+(6))/2→(12); ((7)+(8))/2→(13); ((6)+(8))/2→(14);((7)+3×(5))/4→(15); ((7)+2×(15))/3→(16); ((7)+(16))/2→(17);((13)+3×(12))/4→(18); ((13)+2×(18))/3→(19); ((13)+(19))/2→(20).

Also at this time, in case m−x≧3 and n−y≧3 or 2x<m and 2y<n (see FIG.18), a plurality of interpolation methods are used. This is because, insuch a case, it is necessary to select an appropriate one thereofaccording to the length of (m−x) and (n−y). For example, when thelengths of (m−x) and (n−y) are smaller (compression rate is smaller),the linear interpolation method (less finer interpolation method) may beapplied for the white zone, while, when these lengths are larger(compression rate is larger), the three-order interpolation method(finer interpolation method) may be applied for the white zone. There,each of m, n, x and y represents the number of pixels. In the example ofFIG. 18, n=5; m=5, x=2, and y=2. In this case, the gray zone (to whichthe nearest pixel method is applied as mentioned above) has the width ofone pixel, as shown in the figure. This is because, as the image data ofthe gray zone is generated by using the black zone as it is according tothe nearest pixel method, the image quality may be degraded if the grayzone has a wider area in comparison to the area of the black zone.

FIG. 20 illustrates an example of a basic interpolation patternaccording to a seventh embodiment of the present invention. Similar toFIG. 14, 5×5 pixels are used as a unit of color image data, and, bydecompression through interpolation, 5×5 pixels are generated from 2×2pixels in a black zone. Then, for determining pixels other than theblack zone, a plurality of interpolation methods are selectively used.In particular, the pixels adjacent to the four sides of the black zoneare determined as those in a gray zone, and, the image data of thepixels in the gray zone are determined according to a firstinterpolation method while the image data of the pixel in the whitezone, other than the black zone and gray zone, is determine by a secondinterpolation method other than the first interpolation method. Byemploying this basic interpolation pattern, it is possible to maintain ahigh image quality particularly for non-edge image part.

Specifically, in an example shown in FIG. 21, the nearest pixel methodis used for the gray zone, and the linear interpolation method is usedfor the white zone. Thus, the image data of the pixels in the gray zoneis determined as the image data of the pixels in the black zone adjacentthereto respectively, as follow, as shown in the figure: (1)→(1);(2)→(2); (4)→(4); (3)→(3); . . . . On the other hand, the image data onthe pixels in the white zone is determined according to the linearinterpolation method as follows: ((2)+(5))/2→(7); and ((4)+(6))/2→(8).

Also at this time, in case m−x≧3 and n−y≧3 or 2x<m and 2y<n (see FIG.20), a plurality of interpolation methods are used. This is because, insuch a case, it is necessary to select an appropriate one thereofaccording to the length of (m−x) and (n−y). For example, when thelengths of (m−x) and (n−y) are smaller (compression rate is smaller),the linear interpolation method (less finer interpolation method) may beapplied for the white zone, while, when these lengths are larger(compression rate is larger), the three-order interpolation method(finer interpolation method) may be applied for the white zone. There,each of m, n, x and y represents the number of pixels. In the example ofFIG. 20, n=5; m=5, x=2, and y=2. In this case, the gray zone (to whichthe nearest pixel method is applied as mentioned above) has the width ofone pixel, as shown in the figure. This is because, as the image data ofthe gray zone is generated by using the black zone as it is according tothe nearest pixel method, the image quality may be degraded if the grayzone has a large area in comparison to the area of the black zone.

FIG. 22 illustrates an example of a basic interpolation patternaccording to an eighth embodiment of the present invention. Similar toFIG. 14, 5×5 pixels are used as a unit of color image data, and, bydecompression through interpolation, 5×5 pixels are generated from 2×2pixels in a black zone. Then, for determining pixels other than theblack zone, a plurality of interpolation methods are selectively used.In particular, in the example of FIG. 22, similar to the above-describedexample shown in FIG. 18, the pixel having a distance β in acenter-to-center basis from the pixel in the black zone which is longestamong the distances α, β and γ is determined as a white pixel, and, theimage data of the pixels in the gray zone are determined according to afirst interpolation method while the image data of the pixel in thewhite zone is determine by a second interpolation method other than thefirst interpolation method. Also the scheme according to this basicinterpolation pattern is advantageous for maintaining a high imagequality for non-edge image parts.

Specifically, in a example shown in FIG. 23, the nearest pixel method isused for the gray zone, and the linear interpolation method is used forthe white zone. Thus, the image data of the pixels in the gray zone isdetermined as the image data of the pixels adjacent theretorespectively, as follow, as shown in the figure: (1)→(1); (2)→(2);(4)→(4); (3)→(3); . . . . On the other hand, the image data on thepixels in the white zone is determined according to the linearinterpolation method as follows: ((2)+(5))/2→(9); ((4)+(7))/2→(10);((5)+3×(2))/4→(11); ((5)+2×(11))/3→(12); ((5)+(12))/2→(13);((7)+3×(4))/4→(14); ((7)+2×(14))/3→(15); ((7)+(15))/2→(16).

Also at this time, in case m−x≧3 and n−y≧3 or 2x<m and 2y<n (see FIG.22), a plurality of interpolation methods are used. This is because, insuch a case, it is necessary to select an appropriate one thereofaccording to the length of (m−x) and (n−y). For example, when thelengths of (m−x) and (n−y) are smaller (compression rate is smaller),the linear interpolation method (less finer interpolation method) may beapplied for the white zone, while, when these lengths are larger(compression rate is larger), the three-order interpolation method(finer interpolation method) may be applied for the white zone. There,each of m, n, x and y represents the number of pixels. In the example ofFIG. 22, n=5; m=5, x=2, and y=2. In this case, the gray zone (to whichthe nearest pixel method is applied as mentioned above) has the width ofone pixel, as shown in the figure. This is because, as the image data ofthe gray zone is generated by using the black zone as it is according tothe nearest pixel method, the image quality may be degraded if the grayzone has a large area in comparison to the area of the black zone.

FIG. 26 shows a flow chart of operation of the above-described imagedata interpolation method according to the fifth embodiment of thepresent invention. Assuming that 5×5 pixels are regarded as a unit, 2×2pixels of compressed image data are decompressed and restored in a stepS1. Then, the image data of pixels adjacent to these 2×2 pixels or thosebut excluding the farthest pixel(s) are determined through interpolationaccording to a first interpolation method (for example, the nearestpixel method) in a step S2. Then, the image data of the other pixels isdetermined through interpolation according to a second interpolationmethod other than the first interpolation method (for example, thelinear interpolation method), in a step S3.

FIGS. 24 and 25 illustrate an example of image interpolation methodaccording to a variant embodiment of any of the above-described fifththrough eighth embodiments of the present invention in case a pixelgroup generated through interpolation will then undergo transformationprocessing, such as magnification (increase in the number of pixels)processing. In such a case, according to the size-change (change in thenumber of pixels) rate, an appropriate interpolation method is set.

In the example shown in FIG. 24, 2×2 pixels are regarded as a unit, and,the image data on pixels in a white zone is determined by interpolation.In this case, whether a single interpolation method is applied, or aplurality of interpolation methods are selectively applied is determinedaccording to the size-change rate of pixel number change processingwhich will be performed on the thus generated pixels. For example, it isassumed that, a case is assumed where the change-change rate is 2, and,thus, as shown in FIG. 25, the original 2×2 pixels are transformed into4×4 pixels.

FIG. 27 shows a flow chart illustrating the image data interpolationmethod according to the above-mentioned variant embodiment of thepresent invention applied to the above-described case wherein thesize-change processing will be performed after the interpolation. In thefigure, in a step S11, the compressed data of the 1×1 pixel shown inFIG. 24 is decompressed and restored. Then, the image data of at leastpart (only two pixels having the distances in a center-to-center basisfrom the 1×1 pixel shorter, i.e., α and γ, in the example of FIG. 24,for example) of the pixels adjacent to the 1×1 pixel (first zone orblack zone) is determined according to a first interpolation method (forexample, the nearest pixel method) in a step S12. Then, the image dataof the remaining pixel(s) (the pixel having the distance in acenter-to-center basis from the 1×1 pixel longer, i.e., β in the exampleof FIG. 24, for example) is determined according to a secondinterpolation method (for example, the linear interpolation method)other than the first interpolation method in a step S13. Then,processing of changing (increasing in the case shown in FIG. 25) thenumber of pixels is performed on the thus-obtained 2×2 pixels of imagedata, in a step S14.

FIGS. 28 through 35 show flow charts illustrating the above-describedimage data interpolation methods according to ninth through sixteenthembodiments of the present invention.

In FIG. 28, in a step S21, pixels in a first zone (black zone in theexample of FIG. 16, for example) are restored by decompression. In astep S22, the image data on pixels (gray zone in the example of FIG. 16,for example) adjacent to the first zone is determined according to afirst interpolation method (for example, the nearest pixel method).Then, in a step S23, the image data on the remaining pixels isdetermined according to a method (for example, the linear interpolationmethod) other than the first interpolation method).

In FIG. 29, in a step S31, pixels in a first zone (black zone in theexample of FIG. 19, for example) are restored by decompression. In astep S32, the image data on pixels is determined according to aplurality of interpolation methods selectively according to distances ofthe relevant pixels in center-to-center basis from the pixels in thefirst zone (for example, the nearest pixel method is applied to thosenearest to the pixels in the first zone, the linear interpolation methodis applied to those second nearest to the pixels in the first zone, and,then, the third-order interpolation method is applied to the remainingones).

In FIG. 30, in a step S41, pixels in a first zone (black zone in theexample of FIG. 16, for example) are restored by decompression. In astep S42, an interpolation method(s) to be applied is determinedaccording to the size-change (change in the number of pixels) rate ofpixel number changing processing to be performed later. Then, when it isdetermined in the step S42 that a plurality of interpolation methods areselectively applied, the image data of target pixels is determinedaccording to a first interpolation method (for example, the nearestpixel method, i.e., in case of FIG. 14, for the gray zone) determinedaccording to a predetermined condition (for example, the pixel-numberchange rate of pixel-number processing performed later, or the like, asmentioned above) in steps S43-S44, and, then, the image data on theremaining pixels is determined according to another method (for example,the linear interpolation method or three-order interpolation method forthe white zone) in a step S45. When it is determined in the step s42that a signal interpolation method is applied, the image data of thetarget pixels is determined only according to a single interpolationmethod (for example, the nearest pixel method, the linear interpolationmethod or three-order interpolation method described above) determinedaccording to a predetermined condition (for example, the pixel-numberchange rate of pixel-number processing performed later, or the like, asmentioned above) in a step S46.

In FIG. 31, in a step S51, pixels in a first zone (black zone in theexample of FIG. 19, for example) are restored by decompression. In astep S52, the image data on pixels (gray zone in the example of FIG. 16,for example) determined from the pixels adjacent to the first zoneaccording to the pixel distances in center-to-center basis from thefirst zone is determined according to a first interpolation method (forexample, the nearest pixel method). Then, in a step S53, the image dataon the remaining pixels is determined according to a method (forexample, the linear interpolation method or third-order interpolationmethod) other than the first interpolation method.

In FIG. 32, in a step S61, pixels in a first rectangular zone (blackzone in the example of FIG. 14, for example) are restored bydecompression. In a step S62, the image data on pixels (gray zone in theexample of FIG. 14, for example) adjacent to two sides of the firstrectangular zone is determined according to a first interpolation method(for example, the nearest pixel method). Then, in a step S63, the imagedata on the remaining pixels is determined according to a method (forexample, the linear interpolation method or third-order interpolationmethod) other than the first interpolation method.

In FIG. 33, in a step S71, pixels in a first rectangular zone (blackzone in the example of FIG. 20, for example) are restored bydecompression. In a step S72, the image data on pixels (gray zone in theexample of FIG. 20, for example) adjacent to the four sides of the firstrectangular zone is determined according to a first interpolation method(for example, the nearest pixel method). Then, in a step S73, the imagedata on the remaining pixels is determined according to a method (forexample, the linear interpolation method or third-order interpolationmethod) other than the first interpolation method.

In the above-described processes shown in FIGS. 32 and 33, assuming thatthe above-mentioned first zone is of a rectangle of x×y pixels (shown inFIG. 14, for example), a second zone is of a rectangle of m×n pixels(shown in FIG. 14, for example), preferably 2x<m and also 2y<n. Further,the above-mentioned first interpolation method is preferably applied tothe gray zone having the width of not more than x/2 in the case ofprocess shown in FIG. 32, and the above-mentioned first interpolationmethod is preferably applied to the gray zone having the width of notmore than x in the case of process shown in FIG. 33. Further, in theprocess shown in FIG. 32, preferably, m−x≦3 and also n−y≦3.

In FIG. 34, in a step S81, pixels in a first rectangular zone (blackzone in the example of FIG. 18, for example) are restored bydecompression. In a step S82, the image data on pixels (gray zone in theexample of FIG. 18, for example) adjacent to two sides of the firstrectangular zone and also determined according to thecenter-to-center-basis pixel distances from the pixels in the firstrectangular zone is determined according to a first interpolation method(for example, the nearest pixel method). Then, in a step S83, the imagedata on the remaining pixels is determined according to a method (forexample, the linear interpolation method or third-order interpolationmethod) other than the first interpolation method.

In FIG. 35, in a step S91, pixels in a first rectangular zone (blackzone in the example of FIG. 22, for example) are restored bydecompression. In a step S92, the image data on pixels (gray zone in theexample of FIG. 22, for example) adjacent to the four sides of the firstrectangular zone and also determined according to thecenter-to-center-basis pixel distances from the pixels in the first zoneis determined according to a first interpolation method (for example,the nearest pixel method). Then, in a step S93, the image data on theremaining pixels is determined according to a method (for example, thelinear interpolation method or third-order interpolation method) otherthan the first interpolation method.

The present invention may also be realized by using an informationrecording medium such as a CD-ROM, a magneto-optical disk, a DVD-ROM, afloppy disk, a flash memory, or any other medium such as various type ofROM, RAM, or the like in which software programs for causing ageneral-purpose computer or the like to perform any of theabove-described image compressing/thinning-out, imagedecompression/interpolation processing schemes according to theabove-described embodiments of the present invention. In such a case,the above-mentioned information recording medium is loaded into ageneral-purpose computer or the like, which then reads the softwareprograms therefrom, writes them into a memory thereof, again reads outthe programs therefrom in appropriate timing so as to appropriatelyexecute the relevant processing schemes.

Further, the present invention is not limited to the above-describedembodiments, and variations and modifications may be made withoutdeparting from the scope of the present invention.

The present application is based on Japanese priority applications Nos.2000-396434 and 2001-91594, filed on Dec. 27, 2000 and Mar. 28,. 2001,respectively, the entire contents of which are hereby incorporated byreference.

1-4. (canceled)
 5. An image decompressing apparatus comprising: a partinterpolating thinned-out pixels; and a part determining pixels to beused for the interpolation, wherein said part determining the pixel tobe used for interpolation determines such that pixels nearest to thethinned-out pixels may be selected therefor.
 6. The image decompressingapparatus as claimed in claim 5, wherein said part determining the pixelto be used for interpolation for thinned-out pixels determines such thatpixels not included in an original pixel block in which the thinned-outpixels are included may be selected therefor.
 7. The image decompressingapparatus as claimed in claim 5, wherein said part determining the pixelto be used for interpolation determines such that pixels adjacent to anoriginal pixel block via short sides thereof may be selected.
 8. Animage decompressing apparatus comprising: a part performinginterpolation of thinned-out pixels; and a part determining a method ofthe interpolation according to a pixel-number changing rate ofpixel-number changing processing performed after the interpolation suchthat a finer interpolation method be selected as the pixel-numberchanging rate at which the number of pixels is increased becomes larger.9. The image decompressing apparatus as claimed in claim 8, wherein anearest pixel method is selected when the pixel-number changing rage isless than a first threshold, a linear interpolation method is appliedwhen the pixel-number changing rate falls within a range between thefirst threshold and a second threshold, and a three-order interpolationmethod is applied when the pixel-number changing rate is more than thesecond threshold.
 10. An image decompressing apparatus comprising: apart interpolating thinned-out pixels from not-thinned-out pixels; and apart determining an interpolating method applied, wherein said partdetermining an interpolating method applied applies a less finerinterpolation method for thinned-out pixels located nearer to thenot-thinned-out pixels used for the interpolation.
 11. The imagedecompressing apparatus as claimed in claim 10, wherein said partdetermining an interpolating method applied selectively applies aplurality of interpolation methods and determines the interpolationmethod to be applied according to the center-to-center pixels distancesfrom the not-thinned-out pixels.
 12. The image decompressing apparatusas claimed in claim 10, wherein said part determining an interpolatingmethod applied applies a nearest pixel method for thinned-out pixelsnearest to the not-thinned-out pixels used for interpolation, applies atleast one of a linear interpolation method and a third-orderinterpolation method for the other pixels. 13-15. (canceled)
 16. Animage decompressing method comprising the steps of: a) interpolatingthinned-out pixels; and b) determining pixels to be used for theinterpolation, wherein said step b) determines such that pixels nearestto the thinned-out pixels may be applied.
 17. The method as claimed inclaim 16, wherein said step b) determines such that pixels not includedin an original pixel block in which thinned-out pixels are included maybe applied for interpolation of the thinned-out pixels.
 18. The methodas claimed in claim 16, wherein said step b) determines such that pixelsadjacent to an original pixel block in which thinned-out pixels areincluded via short sides thereof may be applied for interpolation of thethinned-out pixels.
 19. An image decompressing method comprising thesteps of: a) performing interpolation of thinned-out pixels; and b)determining a method of the interpolation according to a pixel-numberchanging rate of pixel-number changing processing performed after theinterpolation such that a finer interpolation method be selected as thepixel-number changing rate at which the number of pixels is increasedbecomes larger.
 20. The image decompressing method as claimed in claim19, wherein a nearest pixel method is applied when the pixel-numberchanging rage is less than a first threshold, a linear interpolationmethod is applied when the pixel-number changing rate falls within arange between the first threshold and a second threshold, and athree-order interpolation method is applied when the pixel-numberchanging rate is more than the second threshold.
 21. An imagedecompressing method comprising the steps of: a) interpolatingthinned-out pixels from not-thinned-out pixels; and b) determining aninterpolating method applied, wherein said step b) applies a less finerinterpolation method for thinned-out pixels located nearer to thenot-thinned-out pixels used for the interpolation.
 22. The methods asclaimed in claim 21, wherein said step b) selectively applies aplurality of interpolation methods and determines the interpolationmethod to be applied according to the center-to-center pixels distancesfrom the not-thinned-out pixels.
 23. The method as claimed in claim 21,wherein said step b) applies a nearest pixel method for thinned-outpixels most nearest to the not-thinned-out pixels used forinterpolation, but applies at least one of a linear interpolation methodand a third-order interpolation method for the other pixels. 24-26.(canceled)
 27. A computer-readable information recording medium having asoftware program recorded therein to be read by a general-purposecomputer so as to cause the computer to perform the steps of: a)interpolating thinned-out pixels; and b) determining pixels to be usedfor the interpolation, wherein said step b) determines such that pixelsnearest to the thinned-out pixels may be selected.
 28. Thecomputer-readable information recording medium as claimed in claim 27,wherein the software program is such that said step b) determines suchthat pixels not included in an original pixel block in which thinned-outpixels are included may be applied for interpolation of the thinned-outpixels.
 29. The computer-readable information recording medium asclaimed in claim 27, wherein the software program is such that said stepb) determines such that pixels adjacent to an original pixel block inwhich thinned-out pixels are included via short sides thereof may beapplied for interpolation of the thinned-out pixels.
 30. Acomputer-readable information recording medium having a software programrecorded therein to be read by a general-purpose computer so as to causethe computer to perform the steps of: a) performing interpolation ofthinned-out pixels; and b) determining a method of the interpolationaccording to a pixel-number changing rate of pixel-number changingprocessing performed after the interpolation such that a finerinterpolation method be selected as the pixel-number changing rate atwhich the number of pixels is increased becomes larger.
 31. Thecomputer-readable information recording medium as claimed in claim 30,wherein the software program is such that a nearest pixel method isapplied when the pixel-number changing rage is less than a firstthreshold, a linear interpolation method is applied when thepixel-number changing rate falls within a range between the firstthreshold and a second threshold, and a three-order interpolation methodis applied when the pixel-number changing rate is more than the secondthreshold.
 32. A computer-readable information recording medium having asoftware program recorded therein to be read by a general-purposecomputer so as to cause the computer to perform the steps of: a)interpolating thinned-out pixels from not-thinned-out pixels; and b)determining an interpolating method applied, wherein said step b)applies a less finer interpolation method for thinned-out pixels locatednearer to the not-thinned-out pixels used for the interpolation.
 33. Thecomputer-readable information recording medium as claimed in claim 32,wherein said step b) selectively applies a plurality of interpolationmethods and determines the interpolation method to be applied accordingto the center-to-center pixels distances from the not-thinned-outpixels.
 34. The computer-readable information recording medium asclaimed in claim 32, wherein the software program is such that said stepb) applies a nearest pixel method for thinned-out pixels most nearest tothe not-thinned-out pixels used for interpolation, but applies at leastone of a linear interpolation method and a third-order interpolationmethod for the other pixels.